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Oct 12 · Monday
Another 240 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出 RAG-PIBench，评测 RAG 上下文中提示注入检测器
Published Oct 6
Evaluated models DistilBERT-base-uncased , DeBERTa-v3-base , MiniLM 构建 COUNTER-GEO-BENCH，评测生成式搜索中的 GEO 虚假信息防御
Published Sep 2
Evaluated models Gemma-4-31B-IT , Qwen-3.5-35B-A3B , Llama-4-Scout-17B-16E and others8 Abstract 论文构建了针对 GEO 虚假信息的首个防御基准，揭示通用护栏的失效与反作用，并提出了有效的轻量对比检测基线。
提出 LeakGauge，用行为后缀的 prefill 对数概率检测上下文泄露
Published Aug 18
Evaluated models Gemma-4-E4B-it , Gemma-4-31B-it , Qwen2.5-14B-Instruct and others11 提出策略 RAG 的知识库投毒攻击与检测防御 CLD-KB
Published Jul 6
Evaluated models Llama 3.2 提出 SeTox 检索增强框架，检测中文新词的隐性毒性
Published Jul 5
Evaluated models SeTox-Qwen2.5-7B Abstract SeTox 用检索把公共共识接入静态 LLM，以检测中文毒性新词。SeTox 研究中文新词上的隐性毒性检测：词表加检索增强，使静态 LLM 在不重训练的情况下利用公开网页上下文。
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